| Practical and configurable network traffic classification using probabilistic machine learning | 0 | 0.34 | 2022 |
| Normalization of Language Embeddings for Cross-Lingual Alignment | 0 | 0.34 | 2022 |
| Quantized Wasserstein Procrustes Alignment of Word Embedding Spaces. | 0 | 0.34 | 2022 |
| Efficient and Oblivious Query Processing for Range and kNN Queries | 0 | 0.34 | 2022 |
| OSCaR - Orthogonal Subspace Correction and Rectification of Biases in Word Embeddings. | 0 | 0.34 | 2021 |
| Constrained Non-Affine Alignment of Embeddings | 0 | 0.34 | 2021 |
| Semantic embedding for regions of interest | 0 | 0.34 | 2021 |
| Finding an Approximate Mode of a Kernel Density Estimate. | 0 | 0.34 | 2021 |
| A Visual Tour of Bias Mitigation Techniques for Word Representations | 0 | 0.34 | 2021 |
| Spatial Independent Range Sampling | 1 | 0.35 | 2021 |
| An Interactive Visual Demo of Bias Mitigation Techniques for Word Representations From a Geometric Perspective. | 0 | 0.34 | 2021 |
| At-the-time and Back-in-time Persistent Sketches | 0 | 0.34 | 2021 |
| The VC Dimension of Metric Balls under Frechet and Hausdorff Distances | 1 | 0.35 | 2021 |
| The GaussianSketch for Almost Relative Error Kernel Distance | 0 | 0.34 | 2020 |
| On Measuring And Mitigating Biased Inferences Of Word Embeddings | 0 | 0.34 | 2020 |
| Independent Range Sampling, Revisited Again. | 0 | 0.34 | 2019 |
| The Kernel Spatial Scan Statistic. | 0 | 0.34 | 2019 |
| Learning In Practice: Reasoning About Quantization. | 0 | 0.34 | 2019 |
| Simple Distances for Trajectories via Landmarks. | 0 | 0.34 | 2019 |
| Closed Form Word Embedding Alignment | 0 | 0.34 | 2019 |
| Scalable Spatial Scan Statistics for Trajectories | 1 | 0.35 | 2019 |
| The VC Dimension of Metric Balls under Fréchet and Hausdorff Distances. | 0 | 0.34 | 2019 |
| Fully Convolutional Structured Lstm Networks For Joint 4d Medical Image Segmentation | 0 | 0.34 | 2018 |
| Improved Coresets for Kernel Density Estimates. | 0 | 0.34 | 2018 |
| A Data-Dependent Distance for Regression. | 0 | 0.34 | 2018 |
| Relative Error RKHS Embeddings for Gaussian Kernels. | 0 | 0.34 | 2018 |
| Improved Bounds on Information Dissemination by Manhattan Random Waypoint Model. | 0 | 0.34 | 2018 |
| Computing Approximate Statistical Discrepancy. | 1 | 0.43 | 2018 |
| Practical Low-Dimensional Halfspace Range Space Sampling. | 0 | 0.34 | 2018 |
| Absolute Orientation for Word Embedding Alignment. | 0 | 0.34 | 2018 |
| Near-Optimal Coresets of Kernel Density Estimates. | 3 | 0.38 | 2018 |
| Approximating the Distribution of the Median and other Robust Estimators on Uncertain Data. | 0 | 0.34 | 2018 |
| Distributed trajectory similarity search | 20 | 0.65 | 2017 |
| An integrated classification scheme for mapping estimates and errors of estimation from the American Community Survey. | 1 | 0.48 | 2017 |
| Nearest-Neighbor Searching Under Uncertainty II | 1 | 0.35 | 2017 |
| Relative Error Embeddings for the Gaussian Kernel Distance. | 1 | 0.35 | 2017 |
| Distributed Trajectory Similarity Search. | 0 | 0.34 | 2017 |
| Visualization of Big Spatial Data Using Coresets for Kernel Density Estimates | 0 | 0.34 | 2017 |
| Visualizing Sensor Network Coverage with Location Uncertainty | 0 | 0.34 | 2017 |
| Coresets for Kernel Regression. | 2 | 0.37 | 2017 |
| epsilon-Kernel Coresets for Stochastic Points. | 0 | 0.34 | 2016 |
| Nearest neighbor searching under uncertainty II | 4 | 0.39 | 2016 |
| Coresets and Sketches | 12 | 0.56 | 2016 |
| Approximate Distribution of L1 Median on Uncertain Data. | 0 | 0.34 | 2016 |
| Scalable spatial scan statistics through sampling. | 0 | 0.34 | 2016 |
| Efficient Frequent Directions Algorithm for Sparse Matrices. | 7 | 0.43 | 2016 |
| The Robustness of Estimator Composition. | 0 | 0.34 | 2016 |
| L∞ Error and Bandwidth Selection for Kernel Density Estimates of Large Data | 3 | 0.41 | 2015 |
| Frequent Directions : Simple and Deterministic Matrix Sketching. | 4 | 0.39 | 2015 |
| Subsampling in Smoothed Range Spaces | 0 | 0.34 | 2015 |
